Hands On Machine Learning with Scikit Learn and TensorFlow

Hands On Machine Learning with Scikit Learn and TensorFlow Author Aurélien Géron
ISBN-10 9781491962244
Release 2017-03-13
Pages 576
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Graphics in this book are printed in black and white. Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—scikit-learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use scikit-learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets Apply practical code examples without acquiring excessive machine learning theory or algorithm details



Python Deep Learning

Python Deep Learning Author Valentino Zocca
ISBN-10 9781786460660
Release 2017-04-28
Pages 406
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Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python. About This Book Explore and create intelligent systems using cutting-edge deep learning techniques Implement deep learning algorithms and work with revolutionary libraries in Python Get real-world examples and easy-to-follow tutorials on Theano, TensorFlow, H2O and more Who This Book Is For This book is for Data Science practitioners as well as aspirants who have a basic foundational understanding of Machine Learning concepts and some programming experience with Python. A mathematical background with a conceptual understanding of calculus and statistics is also desired. What You Will Learn Get a practical deep dive into deep learning algorithms Explore deep learning further with Theano, Caffe, Keras, and TensorFlow Learn about two of the most powerful techniques at the core of many practical deep learning implementations: Auto-Encoders and Restricted Boltzmann Machines Dive into Deep Belief Nets and Deep Neural Networks Discover more deep learning algorithms with Dropout and Convolutional Neural Networks Get to know device strategies so you can use deep learning algorithms and libraries in the real world In Detail With an increasing interest in AI around the world, deep learning has attracted a great deal of public attention. Every day, deep learning algorithms are used broadly across different industries. The book will give you all the practical information available on the subject, including the best practices, using real-world use cases. You will learn to recognize and extract information to increase predictive accuracy and optimize results. Starting with a quick recap of important machine learning concepts, the book will delve straight into deep learning principles using Sci-kit learn. Moving ahead, you will learn to use the latest open source libraries such as Theano, Keras, Google's TensorFlow, and H20. Use this guide to uncover the difficulties of pattern recognition, scaling data with greater accuracy and discussing deep learning algorithms and techniques. Whether you want to dive deeper into Deep Learning, or want to investigate how to get more out of this powerful technology, you'll find everything inside. Style and approach Python Machine Learning by example follows practical hands on approach. It walks you through the key elements of Python and its powerful machine learning libraries with the help of real world projects.



Gizli devlet

Gizli devlet Author Suat Parlar
ISBN-10 STANFORD:36105122797702
Release 2005
Pages 383
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Gizli devlet has been writing in one form or another for most of life. You can find so many inspiration from Gizli devlet also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Gizli devlet book for free.



E imle tan may unutmu uz

E  imle tan    may   unutmu  uz Author Sema Maraşlı
ISBN-10 605536509X
Release 2013
Pages 157
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E imle tan may unutmu uz has been writing in one form or another for most of life. You can find so many inspiration from E imle tan may unutmu uz also informative, and entertaining. Click DOWNLOAD or Read Online button to get full E imle tan may unutmu uz book for free.



Esimin Esi Yok

Esimin Esi Yok Author Sema Marasli
ISBN-10 9759966581
Release 2014-11-01
Pages 192
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Esimin Esi Yok has been writing in one form or another for most of life. You can find so many inspiration from Esimin Esi Yok also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Esimin Esi Yok book for free.



Sevmek Bu Kadar G zelken

Sevmek Bu Kadar G  zelken Author Seth Godin
ISBN-10 9759966611
Release 2014-11-01
Pages 192
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Sevmek Bu Kadar G zelken has been writing in one form or another for most of life. You can find so many inspiration from Sevmek Bu Kadar G zelken also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Sevmek Bu Kadar G zelken book for free.



B y k Resmi G rmek

B  y  k Resmi G  rmek Author Deniz Ülke Aribogan
ISBN-10 6050810648
Release 2013-06-01
Pages 240
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B y k Resmi G rmek has been writing in one form or another for most of life. You can find so many inspiration from B y k Resmi G rmek also informative, and entertaining. Click DOWNLOAD or Read Online button to get full B y k Resmi G rmek book for free.



Inanc Psikolojisi

Inanc Psikolojisi Author Nevzat Tarhan
ISBN-10 9752638651
Release 2013-03-01
Pages 256
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Inanc Psikolojisi has been writing in one form or another for most of life. You can find so many inspiration from Inanc Psikolojisi also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Inanc Psikolojisi book for free.



Esim Askim Olsun

Esim Askim Olsun Author Sema Marasli
ISBN-10 9759966751
Release 2015-01-01
Pages 214
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Esim Askim Olsun has been writing in one form or another for most of life. You can find so many inspiration from Esim Askim Olsun also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Esim Askim Olsun book for free.



Python Data Analysis

Python Data Analysis Author Armando Fandango
ISBN-10 9781787127920
Release 2017-03-27
Pages 330
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Learn how to apply powerful data analysis techniques with popular open source Python modules About This Book Find, manipulate, and analyze your data using the Python 3.5 libraries Perform advanced, high-performance linear algebra and mathematical calculations with clean and efficient Python code An easy-to-follow guide with realistic examples that are frequently used in real-world data analysis projects. Who This Book Is For This book is for programmers, scientists, and engineers who have the knowledge of Python and know the basics of data science. It is for those who wish to learn different data analysis methods using Python 3.5 and its libraries. This book contains all the basic ingredients you need to become an expert data analyst. What You Will Learn Install open source Python modules such NumPy, SciPy, Pandas, stasmodels, scikit-learn,theano, keras, and tensorflow on various platforms Prepare and clean your data, and use it for exploratory analysis Manipulate your data with Pandas Retrieve and store your data from RDBMS, NoSQL, and distributed filesystems such as HDFS and HDF5 Visualize your data with open source libraries such as matplotlib, bokeh, and plotly Learn about various machine learning methods such as supervised, unsupervised, probabilistic, and Bayesian Understand signal processing and time series data analysis Get to grips with graph processing and social network analysis In Detail Data analysis techniques generate useful insights from small and large volumes of data. Python, with its strong set of libraries, has become a popular platform to conduct various data analysis and predictive modeling tasks. With this book, you will learn how to process and manipulate data with Python for complex analysis and modeling. We learn data manipulations such as aggregating, concatenating, appending, cleaning, and handling missing values, with NumPy and Pandas. The book covers how to store and retrieve data from various data sources such as SQL and NoSQL, CSV fies, and HDF5. We learn how to visualize data using visualization libraries, along with advanced topics such as signal processing, time series, textual data analysis, machine learning, and social media analysis. The book covers a plethora of Python modules, such as matplotlib, statsmodels, scikit-learn, and NLTK. It also covers using Python with external environments such as R, Fortran, C/C++, and Boost libraries. Style and approach The book takes a very comprehensive approach to enhance your understanding of data analysis. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work. Packed with clear, easy to follow examples, this book will turn you into an ace data analyst in no time.



B t n Isimler

B  t  n Isimler Author Jose Saramago
ISBN-10 6055340224
Release 2014-06-01
Pages 256
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B t n Isimler has been writing in one form or another for most of life. You can find so many inspiration from B t n Isimler also informative, and entertaining. Click DOWNLOAD or Read Online button to get full B t n Isimler book for free.



Learning Data Mining with Python Second Edition

Learning Data Mining with Python   Second Edition Author Robert Layton
ISBN-10 1787126781
Release 2017-04-28
Pages 413
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Harness the power of Python to analyze data and create insightful predictive modelsAbout This Book* Learn data mining in practical terms, using a wide variety of Python libraries and techniques.* Learn how to find, manipulate, analyze and visualize data using Python.* Step-by-step instructions on creating real-world applications of data mining techniques with PythonWho This Book Is ForIf you are a Python programmer who wants to get started with data mining, then this book is for you. If you are a data analyst who wants to leverage the power of Python to perform data mining efficiently, this book will also help you. No previous experience with data mining is expected.What You Will Learn* Apply data mining concepts to real-world problems* Predict the outcome of sports matches based on past results* Determine the author of a document based on their writing style* Use APIs to download datasets from social media and other online services* Find and extract good features from difficult datasets* Create models that solve real-world problems* Design and develop data mining applications using a variety of datasets* Perform object detection in images using Deep Neural Networks* Find meaningful insights from your data through intuitive visualizations* Compute on big data, including real-time data from the internetIn DetailThe next step in the information age is to gain insights from the deluge of data coming our way. Data mining provides a way of finding these insights, and Python is one of the most popular languages for data mining, providing both power and flexibility in analysis.This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. There is a rich and varied set of libraries available in Python for data mining. This book covers a large number of these libraries, including the IPython Notebook, pandas, scikit-learn, and NLTK.You will also get hands-on experience with a text mining exercise, and see its importance in usage of modern internet. Next, we move on to more complex data types including text, images, and graphs. In every chapter, we create models that solve real-world problems. Further on, you will also discover object detection using Deep Neural Networks, which is one of the big, difficult areas of machine learning right now.With restructured examples and code samples updated for the latest edition of Python, each chapter of this book introduces you to new algorithms and techniques.By the end of the book, you will have great insights into using Python for data mining, and a good knowledge and understanding of the algorithms and implementations.



S merlerin Kurnaz Tanrisi Enki

S  merlerin Kurnaz Tanrisi Enki Author Samuel Noah Kramer
ISBN-10 9758240331
Release 2000
Pages 461
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S merlerin Kurnaz Tanrisi Enki has been writing in one form or another for most of life. You can find so many inspiration from S merlerin Kurnaz Tanrisi Enki also informative, and entertaining. Click DOWNLOAD or Read Online button to get full S merlerin Kurnaz Tanrisi Enki book for free.



Python Data Analysis Second Edition

Python Data Analysis   Second Edition Author Armando Fandango
ISBN-10 1787127486
Release 2017-03-31
Pages 409
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Learn how to apply powerful data analysis techniques with popular open source Python modulesAbout This Book* Find, manipulate, and analyze your data using the Python 3.5 libraries* Perform advanced, high performance linear algebra and mathematical calculations with clean and efficient Python code* An easy-to-follow guide with realistic examples that are frequently used in real-world data analysis projectsWho This Book Is ForThis book is for programmers, scientists, and engineers who have the knowledge of Python and know the basics of data science. It is for those who wish to learn different data analysis methods using Python 3.5 and its libraries.This book contains all the basic ingredients you need to become an expert data analyst.What you will learn* Install open source Python modules like NumPy, SciPy, Pandas, stasmodels, scikit-learn, theano, keras, and tensorflow on various platforms* Prepare, clean your data, and use it for exploratory analysis* Manipulate your data with Pandas* Retrieve and store your data from RDBMS, NoSQL, and Distributed Filesystems such as HDFS and HDF5* Visualize your data with open source libraries such as matplotlib, bokeh, plotly* Learn about various Machine Learning methods such as supervised, unsupervised, probabilistic and bayesian.* Understand signal processing and time-series data analysis* Get to grips with Graph processing, Deep Learning and EnsemblesIn DetailData analysis allows making sense of heaps of data. Python, with its strong set of libraries, is a popular language used today to conduct various data analysis, machine learning and visualization tasks.With this book, you will learn about data analysis with Python in the broadest sense possible, covering everything from data retrieval, cleaning, manipulation, visualization, and storage to complex analysis and modeling. It focuses on a plethora of open source Python modules such as NumPy, SciPy, matplotlib, pandas, IPython, Cython, scikit-learn, and NLTK. In later chapters, the book covers topics such as data visualization, signal processing, and time-series analysis, databases, predictive analytics and machine learning. This book will turn you into an ace data analyst in no time.